Prediction of axillary nodal burden in patients with invasive lobular carcinoma using MRI

A multivariable model of ultrasound and clinicopathological features for predicting axillary nodal burden of breast cancer: potential to prevent unnecessary axillary lymph node dissection

BACKGROUND

To develop a clinical model for predicting high axillary nodal burden in patients with early breast cancer by integrating ultrasound (US) and clinicopathological features.

METHODS AND MATERIALS

Patients with breast cancer who underwent preoperative US examination and breast surgery at the Affiliated Hospital of Nantong University (centre 1, n = 250) and at the Affiliated Hospital of Jiangsu University (centre 2, n = 97) between January 2012 and December 2016 and between January 2020 and March 2022, respectively, were deemed eligible for this study (n = 347). According to the number of lymph node (LN) metastasis based on pathology, patients were divided into two groups: limited nodal burden (0-2 metastatic LNs) and heavy nodal burden (≥ 3 metastatic LNs). In addition, US features combined with clinicopathological variables were compared between these two groups. Univariate and multivariate logistic regression analysis were conducted to identify the most valuable variables for predicting ≥ 3 LNs in breast cancer. A nomogram was then developed based on these independent factors.

RESULTS

Univariate logistic regression analysis revealed that the cortical thickness (p < 0.001), longitudinal to transverse ratio (p = 0.001), absence of hilum (p < 0.001), T stage (p = 0.002) and Ki-67 (p = 0.039) were significantly associated with heavy nodal burden. In the multivariate logistic regression analysis, cortical thickness (p = 0.001), absence of hilum (p = 0.042) and T stage (p = 0.012) were considered independent predictors of high-burden node. The area under curve (AUC) of the nomogram was 0.749.

CONCLUSION

Our model based on US variables and clinicopathological characteristics demonstrates that can help select patients with ≥ 3 LNs, which can in turn be helpful to predict high axillary nodal burden in early breast cancer patients and prevent unnecessary axillary lymph node dissection.

Nomogram based on multiparametric analysis of early-stage breast cancer: Prediction of high burden metastatic axillary lymph nodes

BACKGROUND

The Z0011 and AMAROS trials found that axillary lymph node dissection (ALND) was no longer mandatory for early-stage breast cancer patients who had one or two metastatic axillary lymph nodes (mALNs). The aim of our study was to establish a nomogram which could be used to quantitatively predict the individual likelihood of high burden mALN (≥3 mALN).

METHODS

We retrospectively analyzed 564 women with early breast cancer who had all undergone both ultrasound (US) and magnetic resonance imaging (MRI) to examine axillary lymph nodes before radical surgery. All the patients were divided into training (n = 452) and validation (n = 112) cohorts by computer-generated random numbers. Their clinicopathological features and preoperative imaging associated with high burden mALNs were evaluated by logistic regression analysis to develop a nomogram for predicting the probability of high burden mALNs.

RESULTS

Multivariate analysis showed that high burden mALNs were significantly associated with replaced hilum and the shortest diameter >10 mm on MRI, with cortex thickness >3 mm on US (p < 0.05 each). These imaging criteria plus higher grade (grades II and III) and quadrant of breast tumor were used to develop a nomogram calculating the probability of high burden mALNs. The AUC of the nomogram was 0.853 (95% CI: 0.790-0.908) for the training set and 0.783 (95% CI: 0.638-0.929) for the validation set. Both internal and external validation evaluated the accuracy of nomogram to be good.

CONCLUSION

A well-discriminated nomogram was developed to predict the high burden mALN in early-stage breast patients, which may assist the breast surgeon in choosing the appropriate surgical approach.

High-accuracy prediction of axillary lymph node metastasis in invasive lobular carcinoma using focal cortical thickening on magnetic resonance imaging

BACKGROUND

Invasive lobular carcinoma (ILC) grows diffusely in a single-cell fashion, sometimes presenting only subtle changes in preoperative imaging; therefore, axillary lymph node (ALN) metastases of ILC are difficult to detect using magnetic resonance imaging (MRI). Preoperative underestimation of nodal burden occurs more frequently in ILC than in invasive ductal carcinoma (IDC), however, the morphological assessment for metastatic ALNs of ILC have not fully been investigated. We hypothesized that the high false-negative rate in ILC is caused by the discrepancy in the MRI findings of ALN metastases between ILC and IDC and aimed to identify the MRI finding with a strong correlation with ALN metastasis of ILC.

METHOD

This retrospective analysis included 120 female patients (mean ± standard deviation age, 57.2 ± 11.2 years) who underwent upfront surgery for ILC at a single center between April 2011 and June 2022. Of the 120 patients, 35 (29%) had ALN metastasis. Using logistic regression, we constructed prediction models based on MRI findings: primary tumor size, focal cortical thickening (FCT), cortical thickness, long-axis diameter (LAD), and loss of hilum (LOH).

RESULTS

The area under the curves were 0.917 (95% confidence interval [CI] 0.869-0.968), 0.827 (95% CI 0.758-0.896), 0.754 (95% CI 0.671-0.837), and 0.621 (95% CI 0.531-0.711) for the FCT, cortical thickness, LAD, and LOH models, respectively.

CONCLUSIONS

FCT may be the most relevant MRI finding for ALN metastasis of ILC, and although its prediction model may lead to less underestimation of the nodal burden, rigorous external validation is required.

Magnetic resonance imaging evaluation of single axillary lymph node metastasis in breast cancer: Emphasis on the location of lymph nodes

To evaluate the frequency and location of abnormal lymph nodes (LNs) in breast cancer patients with a single axillary lymph node (ALN) metastasis on breast magnetic resonance imaging (MRI). We retrospectively reviewed the MRI findings of 219 consecutive patients with breast cancer with single ALN metastasis who were surgically confirmed at our institution between January 2018 and December 2018. The morphological features and locations of the abnormal LN on MRI were analyzed. Pathology reports were reviewed to evaluate the size of the metastases and whether they were sentinel LNs (SLNs). Of the 219 patients with a single ALN metastasis, 56 (25.6%) showed abnormal MRI findings. Of these, 54 (96.4%) had either the lowest or second-lowest LN in the level I axilla. In 184 (91.5%) of 201 patients who underwent SLN biopsy, the metastatic LN were SLN. Macrometastases were found more frequently in cases with abnormal LNs than in those with normal-looking LNs (P = .004). The most frequent morphological feature of metastatic ALNs was a diffuse cortical thickening of 3 to 5 mm (37.5%). Although MRI findings of single ALN metastasis in breast cancer patients are none or minimal, abnormalities are observed in the lowest or second-lowest LN in the lower axilla when present, suggesting the location of the SLNs.

MRI characteristics of breast edema for assessing axillary lymph node burden in early-stage breast cancer: a retrospective bicentric study

OBJECTIVES

To investigate whether breast edema characteristics at preoperative T2-weighted imaging (T2WI) could help evaluate axillary lymph node (ALN) burden in patients with early-stage breast cancer.

METHODS

This retrospective study included women with clinical T1 and T2 stage breast cancer and preoperative MRI examination in two independent cohorts from May 2014 to December 2020. Low (< 3 LNs+) and high (≥ 3 LNs+) pathological ALN (pALN) burden were recorded as endpoint. Breast edema score (BES) was evaluated at T2WI. Univariable and multivariable analyses were performed by the logistic regression model. The added predictive value of BES was examined utilizing the area under the curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI).

RESULTS

A total of 1092 patients were included in this study. BES was identified as the independent predictor of pALN burden in primary (n = 677) and validation (n = 415) cohorts. The analysis using MRI-ALN status showed that BES significantly improved the predictive performance of pALN burden (AUC: 0.65 vs 0.71, p < 0.001; IDI = 0.045, p < 0.001; continuous NRI = 0.159, p = 0.050). These results were confirmed in the validation cohort (AUC: 0.64 vs 0.69, p = 0.009; IDI = 0.050, p < 0.001; continuous NRI = 0.213, p = 0.047). Furthermore, BES was positively correlated with biologically invasive clinicopathological factors (p < 0.05).

CONCLUSIONS

In individuals with early-stage breast cancer, preoperative MRI characteristics of breast edema could be a promising predictor for pALN burden, which may aid in treatment planning.

KEY POINTS

• In this retrospective study of 1092 patients with early-stage breast cancer from two cohorts, the MRI characteristic of breast edema has independent and additive predictive value for assessing axillary lymph node burden. • Breast edema characteristics at T2WI positively correlated with biologically invasive clinicopathological factors, which may be useful for preoperative diagnosis and treatment planning for individual patients with breast cancer.

Non-invasive predictors of axillary lymph node burden in breast cancer: a single-institution retrospective analysis

Purpose

Axillary staging is an important prognostic factor in breast cancer. Sentinel lymph node biopsy (SNB) is currently used to stage patients who are clinically and radiologically node-negative. Since the establishment that axillary node clearance (ANC) does not improve overall survival in breast-conserving surgery for patients with low-risk biological cancers, axillary management has become increasingly conservative. This study aims to identify and assess the clinical predictive value of variables that could play a role in the quantification of axillary burden, including the accuracy of quantifying abnormal axillary nodes on ultrasound.

Methods

A retrospective analysis was conducted of hospital data for female breast cancer patients receiving an ANC at our centre between January 2018 and January 2020. The reference standard for axillary burden was surgical histology following SNB and ANC, allowing categorisation of the patients under ‘low axillary burden’ (2 or fewer pathological macrometastases) or ‘high axillary burden’ (> 2). After exploratory univariate analysis, multivariate logistic regression was conducted to determine relationships between the outcome category and candidate predictor variables: patient age at diagnosis, tumour focality, tumour size on ultrasound and number of abnormal lymph nodes on axillary ultrasound.

Results

One hundred and thirty-five patients were included in the analysis. Logistic regression showed that the number of abnormal lymph nodes on axillary ultrasound was the strongest predictor of axillary burden and statistically significant (P = 0.044), with a sensitivity of 66.7% and specificity of 86.8% (P = 0.011).

Conclusion

Identifying the number of abnormal lymph nodes on preoperative ultrasound can help to quantify axillary nodal burden and identify patients with high axillary burden, and should be documented as standard in axillary ultrasound reports of patients with breast cancer.

Invasive Lobular Breast Cancer: Data to Support Surgical Decision Making

BACKGROUND

Invasive lobular carcinoma (ILC) is thought be a unique entity with higher rates of multifocal/multicentric and bilateral disease. This study aimed to evaluate the true extent of the disease, risk of bilaterality, lymph node involvement, and impact of preoperative imaging to help guide surgical decision making.

METHODS

A retrospective analysis identified patients treated for ILC between 2004 and 2017. Clinical staging and pathologic results were compared. Follow-up details including local recurrence, contralateral breast cancer (CBC), and survival outcomes were evaluated.

RESULTS

The study identified 692 patients with ILC, including 43 patients (6%) with a diagnosis of CBC and 232 patients (33%) with a diagnosis of multifocal/multicentric disease at presentation. Preoperative magnetic resonance imaging (MRI) led to an identification of additional disease in 20% of the patients. Preoperative MRI resulted in a more accurate prediction of tumor size staging but did not improve the discordance between clinical and pathologic nodal staging. Overall, the rate of imaging occult lymph node disease was 24%. At the 6-year follow-up evaluation, a local recurrence had developed in 2.3%, a CBC in 2.3, and a distant metastasis in 9.4% of the patients. The overall survival rate was 96% at 3 years and 91% at 5 years.

CONCLUSIONS

Invasive lobular carcinoma is a distinct subset of cancer that poses a diagnostic staging challenge. The results of this study favor MRI for accurate tumor staging and for improving detection of multicentricity and bilaterality. However, clinicians should be aware of the higher likelihood of occult lymph node involvement with ILC and subsequent early metastasis.